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dc.contributor.authorChaorai Kanchanomaien_US
dc.contributor.authorShintaroh Ohashien_US
dc.contributor.authorDaruni Naphromen_US
dc.contributor.authorWakana Nemotoen_US
dc.contributor.authorPhonkrit Maniwaraen_US
dc.contributor.authorKazuhiro Nakanoen_US
dc.date.accessioned2020-10-14T08:22:48Z-
dc.date.available2020-10-14T08:22:48Z-
dc.date.issued2020-08-01en_US
dc.identifier.issn22113460en_US
dc.identifier.issn22113452en_US
dc.identifier.other2-s2.0-85087302704en_US
dc.identifier.other10.1007/s13580-020-00256-4en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087302704&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/69994-
dc.description.abstract© 2020, Korean Society for Horticultural Science. Near-infrared (NIR) spectroscopy is a useful technique for the non-destructive analysis of fruit quality. The key quality parameters of table grapes (Vitis vinifera) that affect consumer preference are the soluble solids content (SSC), pH, firmness, and seedlessness. This research focused on using NIR spectroscopy for assessing the quality of ‘Kyoho’ table grapes, as a non-destructive analysis under laboratory and field conditions. NIR spectra for each sample were acquired in the wavelength range of 400–1000 nm, using a visible/NIR spectrometer with fibre optics in the interactance mode. Partial least-square regression was used to calibrate the NIR spectral data with all the measured properties of table grapes. The best prediction model for firmness was the Savitzky–Golay first derivative (SGD1) with a coefficient of determination (Rprediction2) of 0.7427 in the laboratory, and 0.7804 in the field. The Rprediction2 values for pH in the laboratory and the field was 0.6276 using multiplicative scatter correction (MSC), and 0.7676 using SGD1, respectively. These values were similar to the Rprediction2 values of SSC, which were 0.6926 using MSC, and 0.8052 using the Savitzky–Golay second derivative, respectively. In both analyses the R2 of the calibration model was between 0.6944 and 0.8877. The partial least-square discriminant analysis was used to classify the percentage of seedlessness, which was 93.10% in the laboratory using SGD1 or MSC, and 79.31% in the field using MSC. Therefore, NIR spectroscopy is an efficient non-destructive technique for rapidly analysing Japanese table grape qualities in laboratory and field settings.en_US
dc.subjectAgricultural and Biological Sciencesen_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.titleNon-destructive analysis of Japanese table grape qualities using near-infrared spectroscopyen_US
dc.typeJournalen_US
article.title.sourcetitleHorticulture Environment and Biotechnologyen_US
article.volume61en_US
article.stream.affiliationsNiigata Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
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